Servo control technology is widely used in the fields of robots, high speed rails, electric vehicles, numerical control machine tools, aviation, aerospace, etc. In order to obtain a high-performance closed-loop servo control system, following two basic problems have to be solved: (1) how to obtain feedback information necessary for a closed loop control; and (2) how to design a control strategy or algorithm to meet the requirement for servo control system.
For the former, in terms of servo system, the required feedback information relates to current, voltage, speed, position, etc., wherein the current (or voltage) information can be directly measured by Hall sensor or shunt resistance The position information can be directly detected by means of sensor such as tachogenerator, encoder or resolver. The speed information is usually acquired indirectly through difference of position information. Of course, in some occasions, the position information may also be obtained indirectly using observer technology through measured current and applied voltage to realize so-called position-sensorless scheme.
For the latter, the most widely applied control algorithm in practical servo control system is still PID-based control strategy. In addition, linear control strategy including pole configuration, zero-pole points cancellation and other nonlinear control strategies such as sliding mode variable structure strategy using switching control, model reference adaptive control (MRAC) strategy based on reference model, etc.
It should be noted that PID control has following advantages: (1) good tracking ability for the step input; (2) good steady state performance with zero static deviation; and (3) low susceptibility under disturbance in the loop. However, PID control strategy is only suitable for linear objects or non-linear objects with little variation around operating point. Once the disturbance is too large, the operating point varies widely or the controlled object has too much degree of non-linearity exists, the PID control strategy fails to work properly. Besides, since PID control algorithm is built based on model, it is helpless for unmodeled dynamics.
Although sliding mode variable structure control strategy can be applied to non-linear objects and results in fast dynamic response and also robustness to variation of structure parameters, but there exist chattering problem due to delay in actual switching and control cycle.
MRAC is robust to variation of structure parameters, but dynamic performance in drive system becomes worse and thus has certain limitations in its application.
High-performance servo control system implemented with excellent control algorithm has following features:
(1) good dynamic and steady-state performance; (2) wide adjustable speed range; (3) strong robustness to various disturbances; (4) insensitivity to variation of structural parameters; and (5) immunity to unmodeled dynamics and other non-linear factors.
With the development of technology, more and more equipment have higher need in performance of servo system. Existing control algorithms have difficulty in further meeting these high-performance requirements.
PID control parameters of a current loop in classic servo control scheme are designed according to resistance and inductance parameters of armature (or stator) winding without considering the influence of CEMF; PID control parameters in a speed loop are determined according to inertia of driving system and damping coefficient without considering the influence of load torque; typically, these systems take CEMF of the armature winding and the load torque as disturbances. These disturbances are partly eliminated by means of PID control strategy.
However, in practical situation, when the driving system operates at high speed or its speed changes greatly, the CEMF occupies a large proportion among the entire input voltage. Similarly, when the load torque is large or varies greatly, the load torque becomes dominant among the whole electromagnetic torque. How to deal with these two disturbances is still a challenge in order to improve performance of the servo system.
Through a comprehensive analysis on the existing servo system, the following problems can be found:
(1) Existing scheme has not taken the influence of the CEMF disturbance and the load torque disturbance into account simultaneously, and they are treated separately. So far, servo system schemes available basically adopt a single feed-forward compensation, which either counteract influence of the CEMF by adding a CEMF feed-forward term related to the speed, or counteract influence of the load torque by providing a feed-forward control using detection (or observation) result of the load torque.
(2) Existing schemes have not considered the variations in all electrical parameters (such as resistance, inductance) of the controlled motor (including DC, AC asynchronous and synchronous as well as permanent magnet brushless motors, etc.) and mechanical parameters (such as rotational inertia, stick-slip damping coefficient) of the driving system;
(3) In the existing schemes, disturbance information is mostly acquired by a disturbance observer. Such observer either estimates the load torque or the CEMF itself by using inverse model of the mechanical or electrical portion of the driving system, and then eliminates single disturbance by feed-forward control. Once unknown disturbances are included and model parameters vary, this type of disturbance compensation scheme is greatly discounted. Moreover, since there are unmodeled dynamics at electrical and mechanical portions and other non-linear factors (such as influence of saturation non-linearity on inductance parameters, influence of non-linearity of dynamic and static frictions on load torque, etc.), the conventional disturbance observer has no ability to take all these factors into account in actual motion control system;
(4) Up to now, there have been some schemes which estimate the load torque or CEMF disturbance by extended state observer instead of conventional disturbance observer. It should be noted that such scheme indeed take the influence of unmodeled dynamics, variation in parameters of the drive system and the like into account, and can estimate the variable CEMF or load torque. However, there has been no scheme, so far, which can estimate load torque and CEMF disturbances simultaneously by two extended state observers.